Martini 3 Coarse-Grained Force Field for Cholesterol.

Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol. Here, we describe the development and validation of a Martini 3 cholesterol model, addressing issues related to its bonded setup, shape, volume, and hydrophobicity. The proposed model mitigates some limitations of its Martini 2 predecessor while maintaining or improving the overall behavior.

Localization of the tubby domain, a PI(4,5)P2 biosensor, to E-Syt3-rich endoplasmic reticulum-plasma membrane junctions.

The phospholipid phosphatidylinositol (4,5)-bisphosphate [PI(4,5)P2] acts as a signaling lipid at the plasma membrane (PM) with pleiotropic regulatory actions on multiple cellular processes. Signaling specificity might result from spatiotemporal compartmentalization of the lipid and from combinatorial binding of PI(4,5)P2 effector proteins to additional membrane components. Here, we analyzed the spatial distribution of tubbyCT, a paradigmatic PI(4,5)P2-binding domain, in live mammalian cells by total internal reflection fluorescence (TIRF) microscopy and molecular dynamics simulations. We found that unlike other well-characterized PI(4,5)P2 recognition domains, tubbyCT segregates into distinct domains within the PM. TubbyCT enrichment occurred at contact sites between PM and endoplasmic reticulum (ER) (i.e. at ER-PM junctions) as shown by colocalization with ER-PM markers. Localization to these sites was mediated in a combinatorial manner by binding to PI(4,5)P2 and by interaction with a cytosolic domain of extended synaptotagmin 3 (E-Syt3), but not other E-Syt isoforms. Selective localization to these structures suggests that tubbyCT is a novel selective reporter for a ER-PM junctional pool of PI(4,5)P2. Finally, we found that association with ER-PM junctions is a conserved feature of tubby-like proteins (TULPs), suggesting an as-yet-unknown function of TULPs.

A locally activatable sensor for robust quantification of organellar glutathione.

Glutathione (GSH) is the main determinant of intracellular redox potential and participates in multiple cellular signalling pathways. Achieving a detailed understanding of intracellular GSH homeostasis depends on the development of tools to map GSH compartmentalization and intra-organelle fluctuations. Here we present a GSH-sensing platform for live-cell imaging, termed targetable ratiometric quantitative GSH (TRaQ-G). This chemogenetic sensor possesses a unique reactivity turn-on mechanism, ensuring that the small molecule is only sensitive to GSH in a desired location. Furthermore, TRaQ-G can be fused to a fluorescent protein to give a ratiometric response. Using TRaQ-G fused to a redox-insensitive fluorescent protein, we demonstrate that the nuclear and cytosolic GSH pools are independently regulated during cell proliferation. This sensor was used in combination with a redox-sensitive fluorescent protein to quantify redox potential and GSH concentration simultaneously in the endoplasmic reticulum. Finally, by exchanging the fluorescent protein, we created a near-infrared, targetable and quantitative GSH sensor.

Optimal Bond Constraint Topology for Molecular Dynamics Simulations of Cholesterol.

We recently observed artificial temperature gradients in molecular dynamics (MD) simulations of phase-separating ternary lipid mixtures using the Martini 2 force field. We traced this artifact to insufficiently converged bond length constraints with typical time steps and default settings for the linear constraint solver (LINCS). Here, we systematically optimize the constraint scaffold of cholesterol. With massive virtual sites in an equimomental arrangement, we accelerate bond constraint convergence while preserving the original cholesterol force field and dynamics. The optimized model does not induce nonphysical temperature gradients even at relaxed LINCS settings and is at least as fast as the original model at the strict LINCS settings required for proper thermal sampling. We provide a python script to diagnose possible problems with constraint convergence for other molecules and force fields. Equimomental constraint topology optimization can also be used to boost constraint convergence in atomistic MD simulations of molecular systems.

Two cooperative binding sites sensitize PI(4,5)P2 recognition by the tubby domain.

Phosphoinositides (PIs) are lipid signaling molecules that operate by recruiting proteins to cellular membranes via PI recognition domains. The dominant PI of the plasma membrane is phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]. One of only two PI(4,5)P2 recognition domains characterized in detail is the tubby domain. It is essential for targeting proteins into cilia involving reversible membrane association. However, the PI(4,5)P2 binding properties of tubby domains have remained enigmatic. Here, we used coarse-grained molecular dynamics simulations to explore PI(4,5)P2 binding by the prototypic tubby domain. The comparatively low PI(4,5)P2 affinity of the previously described canonical binding site is underpinned in a cooperative manner by a previously unknown, adjacent second binding site. Mutations in the previously unknown site impaired PI(4,5)P2-dependent plasma membrane localization in living cells and PI(4,5)P2 interaction in silico, emphasizing its importance for PI(4,5)P2 affinity. The two-ligand binding mode may serve to sharpen the membrane association-dissociation cycle of tubby-like proteins that underlies delivery of ciliary cargo.

Small ionic radii limit time step in Martini 3 molecular dynamics simulations.

Among other improvements, the Martini 3 coarse-grained force field provides a more accurate description of the solvation of protein pockets and channels through the consistent use of various bead types and sizes. Here, we show that the representation of Na+ and Cl- ions as "tiny" (TQ5) beads limits the accessible time step to 25 fs. By contrast, with Martini 2, time steps of 30-40 fs were possible for lipid bilayer systems without proteins. This limitation is relevant for systems that require long equilibration times. We derive a quantitative kinetic model of time-integration instabilities in molecular dynamics (MD) as a function of the time step, ion concentration and mass, system size, and simulation time. We demonstrate that ion-water interactions are the main source of instability at physiological conditions, followed closely by ion-ion interactions. We show that increasing the ionic masses makes it possible to use time steps up to 40 fs with minimal impact on static equilibrium properties and dynamical quantities, such as lipid and solvent diffusion coefficients. Increasing the size of the bead representing the ions (and thus changing their hydration) also permits longer time steps. For a soluble protein, we find that increasing the mass of tiny beads also on the protein permits simulations with 30-fs time steps. The use of larger time steps in Martini 3 results in a more efficient exploration of configuration space. The kinetic model of MD simulation crashes can be used to determine the maximum allowed time step upfront for an efficient use of resources and whenever sampling efficiency is critical.

Perspective: a stirring role for metabolism in cells.

Based on recent findings indicating that metabolism might be governed by a limit on the rate at which cells can dissipate Gibbs energy, in this Perspective, we propose a new mechanism of how metabolic activity could globally regulate biomolecular processes in a cell. Specifically, we postulate that Gibbs energy released in metabolic reactions is used to perform work, allowing enzymes to self-propel or to break free from supramolecular structures. This catalysis-induced enzyme movement will result in increased intracellular motion, which in turn can compromise biomolecular functions. Once the increased intracellular motion has a detrimental effect on regulatory mechanisms, this will establish a feedback mechanism on metabolic activity, and result in the observed thermodynamic limit. While this proposed explanation for the identified upper rate limit on cellular Gibbs energy dissipation rate awaits experimental validation, it offers an intriguing perspective of how metabolic activity can globally affect biomolecular functions and will hopefully spark new research.

Hypothesis-Driven, Structure-Based Design in Photopharmacology: The Case of eDHFR Inhibitors.

Photopharmacology uses light to regulate the biological activity of drugs. This precise control is obtained through the incorporation of molecular photoswitches into bioactive molecules. A major challenge for photopharmacology is the rational design of photoswitchable drugs that show light-induced activation. Computer-aided drug design is an attractive approach toward more effective, targeted design. Herein, we critically evaluated different structure-based approaches for photopharmacology with Escherichia coli dihydrofolate reductase (eDHFR) as a case study. Through the iterative examination of our hypotheses, we progressively tuned the design of azobenzene-based, photoswitchable eDHFR inhibitors in five design-make-switch-test-analyze cycles. Targeting a hydrophobic subpocket of the enzyme and a specific salt bridge only with the thermally metastable cis-isomer emerged as the most promising design strategy. We identified three inhibitors that could be activated upon irradiation and reached potencies in the low-nanomolar range. Above all, this systematic study provided valuable insights for future endeavors toward rational photopharmacology.

Protein dynamics and lipid affinity of monomeric, zeaxanthin-binding LHCII in thylakoid membranes.

The xanthophyll cycle in the antenna of photosynthetic organisms under light stress is one of the most well-known processes in photosynthesis, but its role is not well understood. In the xanthophyll cycle, violaxanthin (Vio) is reversibly transformed to zeaxanthin (Zea) that occupies Vio binding sites of light-harvesting antenna proteins. Higher monomer/trimer ratios of the most abundant light-harvesting protein, the light-harvesting complex II (LHCII), usually occur in Zea accumulating membranes and have been observed in plants after prolonged illumination and during high-light acclimation. We present a combined NMR and coarse-grained simulation study on monomeric LHCII from the npq2 mutant that constitutively binds Zea in the Vio binding pocket. LHCII was isolated from 13C-enriched npq2 Chlamydomonas reinhardtii (Cr) cells and reconstituted in thylakoid lipid membranes. NMR results reveal selective changes in the fold and dynamics of npq2 LHCII compared with the trimeric, wild-type and show that npq2 LHCII contains multiple mono- or digalactosyl diacylglycerol lipids (MGDG and DGDG) that are strongly protein bound. Coarse-grained simulations on npq2 LHCII embedded in a thylakoid lipid membrane agree with these observations. The simulations show that LHCII monomers have more extensive lipid contacts than LHCII trimers and that protein-lipid contacts are influenced by Zea. We propose that both monomerization and Zea binding could have a functional role in modulating membrane fluidity and influence the aggregation and conformational dynamics of LHCII with a likely impact on photoprotection ability.

Computational Prediction of ω-Transaminase Specificity by a Combination of Docking and Molecular Dynamics Simulations.

ω-Transaminases (ω-TAs) catalyze the conversion of ketones to chiral amines, often with high enantioselectivity and specificity, which makes them attractive for industrial production of chiral amines. Tailoring ω-TAs to accept non-natural substrates is necessary because of their limited substrate range. We present a computational protocol for predicting the enantioselectivity and catalytic selectivity of an ω-TA from Vibrio fluvialis with different substrates and benchmark it against 62 compounds gathered from the literature. Rosetta-generated complexes containing an external aldimine intermediate of the transamination reaction are used as starting conformations for multiple short independent molecular dynamics (MD) simulations. The combination of molecular docking and MD simulations ensures sufficient and accurate sampling of the relevant conformational space. Based on the frequency of near-attack conformations observed during the MD trajectories, enantioselectivities can be quantitatively predicted. The predicted enantioselectivities are in agreement with a benchmark dataset of experimentally determined ee% values. The substrate-range predictions can be based on the docking score of the external aldimine intermediate. The low computational cost required to run the presented framework makes it feasible for use in enzyme design to screen thousands of enzyme variants.

Computational Redesign of an ω-Transaminase from Pseudomonas jessenii for Asymmetric Synthesis of Enantiopure Bulky Amines.

ω-Transaminases (ω-TA) are attractive biocatalysts for the production of chiral amines from prochiral ketones via asymmetric synthesis. However, the substrate scope of ω-TAs is usually limited due to steric hindrance at the active site pockets. We explored a protein engineering strategy using computational design to expand the substrate scope of an (S)-selective ω-TA from Pseudomonas jessenii (PjTA-R6) toward the production of bulky amines. PjTA-R6 is attractive for use in applied biocatalysis due to its thermostability, tolerance to organic solvents, and acceptance of high concentrations of isopropylamine as amino donor. PjTA-R6 showed no detectable activity for the synthesis of six bicyclic or bulky amines targeted in this study. Six small libraries composed of 7-18 variants each were separately designed via computational methods and tested in the laboratory for ketone to amine conversion. In each library, the vast majority of the variants displayed the desired activity, and of the 40 different designs, 38 produced the target amine in good yield with >99% enantiomeric excess. This shows that the substrate scope and enantioselectivity of PjTA mutants could be predicted in silico with high accuracy. The single mutant W58G showed the best performance in the synthesis of five structurally similar bulky amines containing the indan and tetralin moieties. The best variant for the other bulky amine, 1-phenylbutylamine, was the triple mutant W58M + F86L + R417L, indicating that Trp58 is a key residue in the large binding pocket for PjTA-R6 redesign. Crystal structures of the two best variants confirmed the computationally predicted structures. The results show that computational design can be an efficient approach to rapidly expand the substrate scope of ω-TAs to produce enantiopure bulky amines.

Nonconverged Constraints Cause Artificial Temperature Gradients in Lipid Bilayer Simulations.

Molecular dynamics (MD) simulations have become an indispensable tool to investigate phase separation in model membrane systems. In particular, simulations based on coarse-grained (CG) models have found widespread use due to their increased computational efficiency, allowing for simulations of multicomponent lipid bilayers undergoing phase separation into liquid-ordered and liquid-disordered domains. Here, we show that a significant temperature difference between molecule types can artificially arise in CG MD membrane simulations with the standard Martini simulation parameters in GROMACS. In particular, the linear constraint solver (LINCS) algorithm does not converge with its default settings, resulting in serious temperature differences between molecules in a time step-dependent manner. We demonstrate that the underlying reason for this behavior is the presence of highly constrained moieties, such as cholesterol. Their presence can critically impact numerous structural and dynamic membrane properties obtained from such simulations. Furthermore, any preference of these molecules toward a certain membrane phase can lead to spatial temperature gradients, which can amplify the degree of phase separation or even induce it in compositions that would otherwise mix well. We systematically investigated the effect of the integration time step and LINCS settings on membrane properties. Our data show that for cholesterol-containing membranes, a time step of 20 fs should be combined with at least lincs_iter = 2 and lincs_order = 12, while using a time step of 30 fs requires at least lincs_iter = 3 and lincs_order = 12 to bring the temperature differences to a level where they do not perturb central membrane properties. Moreover, we show that in cases where stricter LINCS settings are computationally too demanding, coupling the lipids in multiple groups to the temperature bath offers a practical workaround to the problem, although the validity of this approach should be further verified. Finally, we show that similar temperature gradients can also emerge in atomistic simulations using the CHARMM force field in combination with settings that allow for a 5 fs integration step.

Biaryl sulfonamides as cisoid azosteres for photopharmacology.

Biaryl sulfonamides are excellent candidates for the azologization approach that yields photoswitchable drugs more active in their metastable cis state, compared to the stable trans state. Here we present the scope and limitations of this strategy for rational design in photopharmacology.

Martini 3: a general purpose force field for coarse-grained molecular dynamics.

The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 ( http://cgmartini.nl ), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein-protein and protein-lipid interactions and material science applications as ionic liquids and aedamers.

Protein-ligand binding with the coarse-grained Martini model.

The detailed understanding of the binding of small molecules to proteins is the key for the development of novel drugs or to increase the acceptance of substrates by enzymes. Nowadays, computer-aided design of protein-ligand binding is an important tool to accomplish this task. Current approaches typically rely on high-throughput docking essays or computationally expensive atomistic molecular dynamics simulations. Here, we present an approach to use the recently re-parametrized coarse-grained Martini model to perform unbiased millisecond sampling of protein-ligand interactions of small drug-like molecules. Remarkably, we achieve high accuracy without the need of any a priori knowledge of binding pockets or pathways. Our approach is applied to a range of systems from the well-characterized T4 lysozyme over members of the GPCR family and nuclear receptors to a variety of enzymes. The presented results open the way to high-throughput screening of ligand libraries or protein mutations using the coarse-grained Martini model.

Molecular dynamics simulations in photosynthesis.

Photosynthesis is regulated by a dynamic interplay between proteins, enzymes, pigments, lipids, and cofactors that takes place on a large spatio-temporal scale. Molecular dynamics (MD) simulations provide a powerful toolkit to investigate dynamical processes in (bio)molecular ensembles from the (sub)picosecond to the (sub)millisecond regime and from the Å to hundreds of nm length scale. Therefore, MD is well suited to address a variety of questions arising in the field of photosynthesis research. In this review, we provide an introduction to the basic concepts of MD simulations, at atomistic and coarse-grained level of resolution. Furthermore, we discuss applications of MD simulations to model photosynthetic systems of different sizes and complexity and their connection to experimental observables. Finally, we provide a brief glance on which methods provide opportunities to capture phenomena beyond the applicability of classical MD.

Unidirectional rotating molecular motors dynamically interact with adsorbed proteins to direct the fate of mesenchymal stem cells.

Artificial rotary molecular motors convert energy into controlled motion and drive a system out of equilibrium with molecular precision. The molecular motion is harnessed to mediate the adsorbed protein layer and then ultimately to direct the fate of human bone marrow-derived mesenchymal stem cells (hBM-MSCs). When influenced by the rotary motion of light-driven molecular motors grafted on surfaces, the adsorbed protein layer primes hBM-MSCs to differentiate into osteoblasts, while without rotation, multipotency is better maintained. We have shown that the signaling effects of the molecular motion are mediated by the adsorbed cell-instructing protein layer, influencing the focal adhesion-cytoskeleton actin transduction pathway and regulating the protein and gene expression of hBM-MSCs. This unique molecular-based platform paves the way for implementation of dynamic interfaces for stem cell control and provides an opportunity for novel dynamic biomaterial engineering for clinical applications.

Capturing Choline-Aromatics Cation-π Interactions in the MARTINI Force Field.

Cation-π interactions play an important role in biomolecular recognition, including interactions between membrane phosphatidylcholine lipids and aromatic amino acids of peripheral proteins. While molecular mechanics coarse grain (CG) force fields are particularly well suited to simulate membrane proteins in general, they are not parameterized to explicitly reproduce cation-π interactions. We here propose a modification of the polarizable MARTINI coarse grain (CG) model enabling it to model membrane binding events of peripheral proteins whose aromatic amino acid interactions with choline headgroups are crucial for their membrane binding. For this purpose, we first collected and curated a dataset of eight peripheral proteins from different families. We find that the MARTINI CG model expectedly underestimates aromatics-choline interactions and is unable to reproduce membrane binding of the peripheral proteins in our dataset. Adjustments of the relevant interactions in the polarizable MARTINI force field yield significant improvements in the observed binding events. The orientation of each membrane-bound protein is comparable to reference data from all-atom simulations and experimental binding data. We also use negative controls to ensure that choline-aromatics interactions are not overestimated. We finally check that membrane properties, transmembrane proteins, and membrane translocation potential of mean force (PMF) of aromatic amino acid side-chain analogues are not affected by the new parameter set. This new version "MARTINI 2.3P" is a significant improvement over its predecessors and is suitable for modeling membrane proteins including peripheral membrane binding of peptides and proteins.

An Allosteric Pathway in Copper, Zinc Superoxide Dismutase Unravels the Molecular Mechanism of the G93A Amyotrophic Lateral Sclerosis-Linked Mutation.

Several different mutations of the protein copper, zinc superoxide dismutase (SOD1) produce the neurodegenerative disorder amyotrophic lateral sclerosis (ALS). The molecular mechanism by which the diverse mutations converge to a similar pathology is currently unknown. The electrostatic loop (EL) of SOD1 is known to be affected in all of the studied ALS-linked mutations of SOD1. In this work, we employ a multiscale simulation approach to show that this perturbation corresponds to an increased probability of the EL detaching from its native position, exposing the metal site of the protein to water. From extensive atomistic and coarse-grained molecular dynamics (MD) simulations, we identify an allosteric pathway that explains the action of the distant G93A mutation on the EL. Finally, we employ quantum mechanics/molecular mechanics MD simulations to show that the opening of the EL decreases the Zn(II) affinity of the protein. As the loss of Zn(II) is at the center of several proposed pathogenic mechanisms in SOD1-linked ALS, the structural effect identified here not only is in agreement with the experimental data but also places the opening of the electrostatic loop as the possible main pathogenic effect for a significant number of ALS-linked SOD1 mutations.

Pitfalls of the Martini Model.

The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.